The present invention relates generally to an improved data processing system and in particular to a method and apparatus for generating cohorts. More particularly, the present invention is directed to a computer implemented method, apparatus, and computer usable program code for processing cohort data to generate receptivity scores.
A cohort is a group of members selected based upon a commonality of one or more attributes. For example, one attribute may be a level of education attained by workers. Thus, a cohort of workers in an office building may include members who have graduated from an institution of higher education. In addition, the cohort of workers may include one or more sub-cohorts that may be identified based upon additional attributes such as, for example, a type of degree attained, a number of years the worker took to graduate, or any other conceivable attribute. In this example, such a cohort may be used by an employer to correlate a worker's level of education with job performance, intelligence, and/or any number of variables. The effectiveness of cohort studies depends upon a number of different factors, such as the length of time that the members are observed, and the ability to identify and capture relevant data for collection. For example, the information that is needed or wanted to identify attributes of potential members of a cohort may be voluminous, dynamically changing, unavailable, difficult to collect, and/or unknown to the members of the cohort and/or the user selecting members of the cohort. Moreover, it may be difficult, time consuming, or impractical to access all the information necessary to accurately generate cohorts. Thus, unique cohorts may be sub-optimal because individuals lack the skill, time, knowledge, and/or expertise needed to gather cohort attribute information from available sources.